I build a price-ratio model based on the Campbell and Shiller (1988) decomposition to test which components of investor expectations best explains cross-sectional price differences. I evaluate the in- and out-of-sample performance of my model, which uses a higher-order expansion with an added...

Abstract We predict cumulative stock returns over horizons from 1 month to 10 years using a tree-based machine learning approach. Cumulative stock returns are significantly predictable in the cross-section over all horizons. A hedge portfolio generates 250 bp/month at a 1 year horizon and 110...

Stock market predictability is of considerable interest in both academic research and investment practice. Ross (2005) provides a simple and elegant upper bound on the predictive regression R-squared that R^2 = (1 R_f)^2 Var(m) for a given asset pricing model with kernel m, where R_f is the...

We study the effect of the home bias on international asset pricing by extending the core-satellite approach of active asset allocation to an equilibrium analysis. In this framework, investors combine a common core portfolio with an active investment in their home asset. In equilibrium, the core...

This paper provides evidence that the market does not efficiently incorporate expected returns implied by analyst price targets into prices. I use a novel decomposition to extract information and bias components from these analyst-expected returns and develop an asset pricing framework that...

Current R&D expenditures forecast cash-based operating profitability up to three years in the future and sometimes as much as ten years, but do not forecast asset growth. High R&D firms have positive loadings on a cash-based operating profitability factor, and zero alphas. Capitalizing R&D to...

The proliferation of anomalies and the resulting `factor zoo' has challenged finance researchers to identify firm characteristics that are genuinely related to the cross-sectional variation in expected stock returns. We address this challenge using a Bayesian ensemble of trees approach, namely,...

We study the problem of detecting structural instability of factor strength in asset pricing models for financial returns. We allow for strong and weaker factors, in which the sum of squared betas grows at a rate equal to and slower than the number of test assets, respectively: this growth rate...

I find no evidence that partial least squares based on disaggregated book-to-market ratios produces a model of market premiums with persistently positive out-of-sample R2, as originally documented for market returns. This is consistent with time variation in predictability, for example, and does...